Journals
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International Journal of Intelligent Systems and Data Science
Building robust, ethical, and scalable intelligent systems requires an integrated approach that recognizes the close interdependence between algorithmic innovation and data-driven reasoning. Advances in artificial intelligence and data science increasingly influence decision-making across science, industry, governance, and society, making it essential to address not only technical performance but also reliability, transparency, and long-term sustainability. This includes developing methods that are resilient to data uncertainty, bias, and distributional shifts, as well as designing systems that can adapt to evolving real-world conditions.
Achieving meaningful progress in intelligent systems demands attention to foundational challenges such as data quality, model interpretability, computational efficiency, and responsible deployment. Equally important are broader structural considerations, including access to data and computational resources, skills development, and the ethical and societal implications of intelligent technologies. Addressing these challenges requires collaboration across disciplines, combining theoretical advances with applied research and empirical validation.
The International Journal of Intelligent Systems and Data Science (IJISDS) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from artificial intelligence, machine learning, data science, and allied domains to deepen understanding of how intelligent systems can be designed, evaluated, and applied responsibly. IJISDS supports research that bridges theory and practice, encouraging contributions that demonstrate both methodological rigor and real-world relevance.
Through its editorial standards and publishing practices, IJISDS actively promotes reproducibility, ethical responsibility, and transparent peer review. The journal also seeks to contribute to broader global priorities by supporting research aligned with sustainable development, digital innovation, and responsible AI, recognizing the critical role that intelligent systems and data science play in shaping resilient and equitable futures.
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International Journal of Clinical Research and Medical Sciences
The International Journal of Clinical Research and Medical Sciences (IJCRMS) publishes rigorously evaluated research that contributes directly to clinical knowledge and medical science. The journal prioritizes studies with clearly defined research questions, appropriate study design, and transparent analytical methodology, particularly where findings have relevance to diagnosis, treatment, disease progression, or healthcare outcomes.
IJCRMS focuses on clinical research, biomedical investigations, and public health studies grounded in empirical evidence. The journal accepts original research articles, systematic reviews, and structured clinical studies, including observational and retrospective analyses. Case-based submissions are considered only when they provide substantial clinical insight or methodological relevance. Purely speculative, opinion-based, or commercially motivated manuscripts are not within the journal’s scope.
All submissions must demonstrate compliance with recognized medical research ethics, including institutional approval where applicable, informed consent, and full disclosure of conflicts of interest. Manuscripts are evaluated through a double-blind peer-review process with explicit criteria for methodological validity, ethical integrity, and contribution to existing medical literature.
IJCRMS is structured to support reproducible, ethically sound medical research and to serve as a stable scholarly record for clinicians and researchers engaged in evidence-based medical practice.
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International Journal of Adaptive Management and Business Intelligence
Building robust, ethical, and scalable organizations requires an integrated approach that recognizes the close interdependence between adaptive management strategies and data-driven business intelligence. As global markets and operational environments become increasingly volatile, it is essential to move beyond static models and embrace systems that prioritize reliability, transparency, and long-term strategic sustainability.
IJAMBI focuses on methods that are resilient to market uncertainty and distributional shifts, specifically designing systems that allow businesses and institutions to adapt to evolving real-world conditions. Achieving meaningful progress in this field demands attention to foundational challenges such as data quality, predictive analytics, computational efficiency, and responsible deployment within corporate and governmental frameworks.
The International Journal of Adaptive Management and Business Intelligence (IJAMBI) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from management science, artificial intelligence, business analytics, and organizational theory to deepen understanding of how intelligent systems can be designed and applied to enhance human decision-making.
IJAMBI supports research that bridges the gap between theoretical frameworks and practical business applications, encouraging contributions that demonstrate both methodological rigor and real-world relevance. Through its editorial standards, the journal promotes reproducibility and ethical responsibility, recognizing the critical role that adaptive systems play in shaping resilient, competitive, and equitable futures.